{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "qS-Y8YxVbSTo"
      },
      "source": [
        "# ECG Signal Categorization Using Wavelet Analysis"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "VxHLX9PVbUul"
      },
      "source": [
        "#### How Does the Wavelet Transform Operate?\n",
        "It is a linear combination of sine waves with varying frequencies. In contrast, the Wavelet Transform uses a set of functions known as wavelets, each operating at a different scale. A wavelet, meaning \"small wave,\" is a function that oscillates for a brief period and then diminishes.\n",
        "\n",
        "The figure above demonstrates the key difference between a sine wave and a wavelet. While sine waves extend infinitely in both directions and lack time localization, wavelets are confined to a specific time interval. This localization allows the Wavelet Transform to provide time and frequency information about the signal.\n",
        "A wavelet is convolved with the signal across its entire length to analyze a signal. Starting at the signal's beginning, the wavelet gradually shifts across time. After analyzing with the original wavelet (called the \"mother wavelet\"), it is scaled (stretched or compressed), and the process is repeated. This approach captures variations at different time and frequency scales, as shown in the illustration below."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "9RqG7yU_MsFT"
      },
      "outputs": [],
      "source": [
        "import pywt\n",
        "import numpy as np\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt \n",
        "\n",
        "from scipy.fftpack import fft\n",
        "from collections import Counter\n",
        "import matplotlib.pyplot as plt\n",
        "import matplotlib.gridspec as gridspec\n",
        "from mpl_toolkits.axes_grid1 import make_axes_locatable\n",
        "\n",
        "import matplotlib.pyplot as plt\n",
        "import matplotlib.gridspec as gridspec\n",
        "import matplotlib.patches as patches\n",
        "\n",
        "import scipy.io as sio\n",
        "import scipy\n",
        "\n",
        "from collections import defaultdict, Counter\n",
        "\n",
        "from sklearn.ensemble import GradientBoostingClassifier\n",
        "from sklearn.preprocessing import StandardScaler, LabelEncoder\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.metrics import classification_report\n",
        "from sklearn.metrics import accuracy_score\n",
        "from sklearn.decomposition import PCA\n",
        "from sklearn.manifold import TSNE\n",
        "\n",
        "from lightgbm import LGBMClassifier"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 54
        },
        "id": "wW_WGZpvYzzh",
        "outputId": "29ef4364-2c82-43de-fb5d-7f8e7a140e84"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "['Haar', 'Daubechies', 'Symlets', 'Coiflets', 'Biorthogonal', 'Reverse biorthogonal', 'Discrete Meyer (FIR Approximation)', 'Gaussian', 'Mexican hat wavelet', 'Morlet wavelet', 'Complex Gaussian wavelets', 'Shannon wavelets', 'Frequency B-Spline wavelets', 'Complex Morlet wavelets']\n"
          ]
        }
      ],
      "source": [
        "print(pywt.families(short=False))"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "uAzto74rTzW8"
      },
      "source": [
        "Each wavelet type has a different shape, smoothness, and compactness, which is helpful for different purposes. Since there are only two mathematical conditions a wavelet has to satisfy, generating a new type of wavelet is easy.\n",
        "\n",
        "The two mathematical conditions are the so-called normalization and orthogonalization constraints:\n",
        "\n",
        "A wavelet must have \n",
        "* finite energy \n",
        "* zero mean\n",
        "\n",
        "*Finite energy* denotes localization in frequency and time; it is integrable, and the inner product between the wavelet and the signal always exists. The admissibility condition implies a wavelet has zero mean in the time domain, a zero at zero frequency. This is necessary to ensure that it is integrable and that the inverse of the wavelet transform can also be calculated."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "lNJkPtGYNDCA"
      },
      "outputs": [],
      "source": [
        "pywt.Wavelet?"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 635
        },
        "id": "U76zCJ0vOKU8",
        "outputId": "b5d2b471-319e-4477-abce-686253d430db"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/numpy/core/numeric.py:492: ComplexWarning: Casting complex values to real discards the imaginary part\n",
            "  return array(a, dtype, copy=False, order=order)\n"
          ]
        },
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 1152x576 with 8 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "output_type": "display_data"
        }
      ],
      "source": [
        "discrete_wavelets = ['db5', 'sym5', 'coif5', 'bior2.4']\n",
        "continuous_wavelets = ['mexh', 'morl', 'cgau5', 'gaus5']\n",
        " \n",
        "list_list_wavelets = [discrete_wavelets, continuous_wavelets]\n",
        "list_funcs = [pywt.Wavelet, pywt.ContinuousWavelet]\n",
        " \n",
        "fig, axarr = plt.subplots(nrows=2, ncols=4, figsize=(16,8))\n",
        "for ii, list_wavelets in enumerate(list_list_wavelets):\n",
        "    func = list_funcs[ii]\n",
        "    row_no = ii\n",
        "    for col_no, waveletname in enumerate(list_wavelets):\n",
        "        wavelet = func(waveletname)\n",
        "        family_name = wavelet.family_name\n",
        "        biorthogonal = wavelet.biorthogonal\n",
        "        orthogonal = wavelet.orthogonal\n",
        "        symmetry = wavelet.symmetry\n",
        "        if ii == 0:\n",
        "            _ = wavelet.wavefun()\n",
        "            wavelet_function = _[0]\n",
        "            x_values = _[-1]\n",
        "        else:\n",
        "            wavelet_function, x_values = wavelet.wavefun()\n",
        "        if col_no == 0 and ii == 0:\n",
        "            axarr[row_no, col_no].set_ylabel(\"Discrete Wavelets\", fontsize=16)\n",
        "        if col_no == 0 and ii == 1:\n",
        "            axarr[row_no, col_no].set_ylabel(\"Continuous Wavelets\", fontsize=16)\n",
        "        axarr[row_no, col_no].set_title(\"{}\".format(family_name), fontsize=16)\n",
        "        axarr[row_no, col_no].plot(x_values, wavelet_function)\n",
        "        axarr[row_no, col_no].set_yticks([])\n",
        "        axarr[row_no, col_no].set_yticklabels([])\n",
        " \n",
        "plt.tight_layout()\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "iITyYkeIUJZ4"
      },
      "source": [
        "DWT is implemented as a cascade of high-pass and low-pass filters. This is because filter banks are a very efficient way of splitting a signal into several frequency sub-bands. Below, I will explain the concept behind the filter bank in a simple (and probably oversimplified) way. It is necessary to understand how the wavelet transform works and how it can be used in practical applications. We start with the most miniature scale to apply the DWT on a signal. As we have seen before, small scales correspond with high frequencies. This means that we first analyze high-frequency behaviour. We examine behaviour at around half of the maximum frequency in the second stage, where the scale increases by a factor of two (the frequency lowers by a factor of two). We are examining frequency behaviour at around a quarter of the maximum frequency at the third level, where the scale factor is four. Moreover, this continues until we have reached the maximum decomposition level.\n",
        "\n",
        "What do we mean by maximum decomposition level?  To understand this, we should also know that at each subsequent stage, the number of samples in the signal is reduced by a factor of two. At lower frequency values, you will need fewer samples to satisfy the Nyquist rate, so there is no need to keep the higher number of samples in the signal; it will only cause the transform to be computationally expensive. Due to this downsampling, at some stage in the process, the number of samples in our signal will become smaller than the length of the wavelet filter, and we will have reached the maximum decomposition level. In the first stage, we split our signal into a low-frequency and a high-frequency part. In the third stage, we split the 0-250 Hz part into 0-125 Hz and 125-250 Hz parts.\n",
        "This goes on until we have reached the refinement level we need or run out of samples.\n",
        "We can easily visualize this idea by plotting what happens when we apply the DWT to a chirp signal. A chirp signal is a signal with a dynamic frequency spectrum; the frequency spectrum increases with time. The start of the signal contains low-frequency values, and the end contains high frequencies. This makes it easy to visualize which part of the frequency spectrum is filtered out by looking at the time axis.\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 537
        },
        "id": "17tJZJoWUJhb",
        "outputId": "809d1141-7b7f-42f5-ef1f-0bb526fc3089"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 432x72 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "output_type": "display_data"
        },
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 432x432 with 10 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "output_type": "display_data"
        }
      ],
      "source": [
        "x = np.linspace(0, 1, num=2048)\n",
        "chirp_signal = np.sin(250 * np.pi * x**2)\n",
        "    \n",
        "fig, ax = plt.subplots(figsize=(6,1))\n",
        "ax.set_title(\"Original Chirp Signal: \")\n",
        "ax.plot(chirp_signal)\n",
        "plt.show()\n",
        "    \n",
        "data = chirp_signal\n",
        "waveletname = 'sym5'\n",
        " \n",
        "fig, axarr = plt.subplots(nrows=5, ncols=2, figsize=(6,6))\n",
        "for ii in range(5):\n",
        "    (data, coeff_d) = pywt.dwt(data, waveletname)\n",
        "    axarr[ii, 0].plot(data, 'r')\n",
        "    axarr[ii, 1].plot(coeff_d, 'g')\n",
        "    axarr[ii, 0].set_ylabel(\"Level {}\".format(ii + 1), fontsize=14, rotation=90)\n",
        "    axarr[ii, 0].set_yticklabels([])\n",
        "    if ii == 0:\n",
        "        axarr[ii, 0].set_title(\"Approximation coefficients\", fontsize=14)\n",
        "        axarr[ii, 1].set_title(\"Detail coefficients\", fontsize=14)\n",
        "    axarr[ii, 1].set_yticklabels([])\n",
        "plt.tight_layout()\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "id": "Ngq-ZakYN0Yc",
        "outputId": "8f46ec7e-acee-4c79-e82a-c03bbcc2c063"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "(2048,)"
            ]
          },
          "execution_count": 19,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "chirp_signal.shape"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "dGHHKQWJUJrZ"
      },
      "source": [
        "Wavelet Transform Coefficients and Their Significance\n",
        "The Discrete Wavelet Transform (DWT) provides two essential outputs at each level of decomposition: approximation coefficients and detail coefficients. The example below demonstrates the application of the sym5 wavelet on a chirp signal across levels 1 to 5, alongside a schematic of the high-pass and low-pass filters applied at each stage.\n",
        "\n",
        "Important Aspects:\n",
        "Estimated The low-pass filter, also known as an averaging filter, is where the coefficients come from.\n",
        "They pick up on the signal's low-frequency elements or general trends.\n",
        "Detail Coefficients: The high-pass filter, often known as the difference filter, provides these.\n",
        "They record the high-frequency or detailed parts of the signal.\n",
        "\n",
        "Several Levels of Decomposition:\n",
        "By applying the DWT recursively to the approximation coefficients from the previous level, we can obtain the wavelet transform for subsequent levels.\n",
        "Each successive level samples the original signal at half the resolution, effectively down-sampling the signal by a factor of 2.\n",
        "This hierarchical decomposition allows for efficient signal analysis, enabling both time and frequency localization of features.\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "FexEo51iUJyx"
      },
      "outputs": [],
      "source": [
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import pywt\n",
        "from scipy.fft import fft\n",
        "\n",
        "# Function to plot Wavelet Transform (Power Spectrum)\n",
        "def plot_wavelet(time, signal, scales, waveletname='cmor', \n",
        "                 cmap=plt.cm.seismic, title='Wavelet Transform (Power Spectrum)',\n",
        "                 ylabel='Period (years)', xlabel='Time'):\n",
        "    \"\"\"\n",
        "    Plots the Wavelet Transform (Power Spectrum) of a given signal.\n",
        "    \"\"\"\n",
        "    dt = time[1] - time[0]  # Time step\n",
        "    coefficients, frequencies = pywt.cwt(signal, scales, waveletname, dt)\n",
        "    power = (np.abs(coefficients)) ** 2  # Compute power spectrum\n",
        "    period = 1. / frequencies  # Convert frequencies to periods\n",
        "\n",
        "    # Define log scale for contours\n",
        "    levels = [0.0625, 0.125, 0.25, 0.5, 1, 2, 4, 8]\n",
        "    contourlevels = np.log2(levels)\n",
        "\n",
        "    # Create the plot\n",
        "    fig, ax = plt.subplots(figsize=(15, 10))\n",
        "    im = ax.contourf(time, np.log2(period), np.log2(power), levels=contourlevels, extend='both', cmap=cmap)\n",
        "    ax.set_title(title, fontsize=20)\n",
        "    ax.set_ylabel(ylabel, fontsize=18)\n",
        "    ax.set_xlabel(xlabel, fontsize=18)\n",
        "\n",
        "    # Customize y-axis (log scale for periods)\n",
        "    yticks = 2 ** np.arange(np.ceil(np.log2(period.min())), np.ceil(np.log2(period.max())))\n",
        "    ax.set_yticks(np.log2(yticks))\n",
        "    ax.set_yticklabels([f'{int(tick)}' for tick in yticks])\n",
        "    ax.invert_yaxis()  # Invert y-axis for wavelet representation\n",
        "    ax.set_ylim(ax.get_ylim()[0], -1)\n",
        "\n",
        "    # Add a colorbar\n",
        "    cbar_ax = fig.add_axes([0.95, 0.5, 0.03, 0.25])\n",
        "    fig.colorbar(im, cax=cbar_ax, orientation=\"vertical\")\n",
        "    plt.show()\n",
        "\n",
        "# Function to compute averaged values over specified intervals\n",
        "def get_ave_values(xvalues, yvalues, n=5):\n",
        "    \"\"\"\n",
        "    Computes averaged values of x and y over n intervals.\n",
        "    \"\"\"\n",
        "    signal_length = len(xvalues)\n",
        "    padding_length = (n - signal_length % n) if signal_length % n != 0 else 0\n",
        "\n",
        "    # Pad arrays if necessary\n",
        "    xarr = np.pad(xvalues, (0, padding_length), constant_values=np.nan)\n",
        "    yarr = np.pad(yvalues, (0, padding_length), constant_values=np.nan)\n",
        "\n",
        "    # Reshape and compute averages\n",
        "    x_reshaped = xarr.reshape(-1, n)\n",
        "    y_reshaped = yarr.reshape(-1, n)\n",
        "    x_ave = x_reshaped[:, 0]  # Take the first value in each interval\n",
        "    y_ave = np.nanmean(y_reshaped, axis=1)  # Compute mean while ignoring NaNs\n",
        "\n",
        "    return x_ave, y_ave\n",
        "\n",
        "# Function to plot signal and its time-averaged version\n",
        "def plot_signal_plus_average(time, signal, average_over=5):\n",
        "    \"\"\"\n",
        "    Plots the signal alongside its time-averaged version.\n",
        "    \"\"\"\n",
        "    time_ave, signal_ave = get_ave_values(time, signal, average_over)\n",
        "\n",
        "    fig, ax = plt.subplots(figsize=(15, 3))\n",
        "    ax.plot(time, signal, label='Signal')\n",
        "    ax.plot(time_ave, signal_ave, label=f'Time Average (n={average_over})', linestyle='--', color='orange')\n",
        "    ax.set_xlim([time[0], time[-1]])\n",
        "    ax.set_ylabel('Signal Amplitude', fontsize=18)\n",
        "    ax.set_title('Signal + Time Average', fontsize=18)\n",
        "    ax.set_xlabel('Time', fontsize=18)\n",
        "    ax.legend()\n",
        "    plt.show()\n",
        "\n",
        "# Function to compute FFT values and frequencies\n",
        "def get_fft_values(y_values, T, N):\n",
        "    \"\"\"\n",
        "    Computes the FFT values and corresponding frequencies.\n",
        "    \"\"\"\n",
        "    f_values = np.linspace(0.0, 1.0 / (2.0 * T), N // 2)  # Frequency axis\n",
        "    fft_values = 2.0 / N * np.abs(fft(y_values)[:N // 2])  # FFT amplitudes\n",
        "    return f_values, fft_values\n",
        "\n",
        "# Function to plot Fourier Transform and Power Spectrum\n",
        "def plot_fft_plus_power(time, signal):\n",
        "    \"\"\"\n",
        "    Plots the Fourier Transform and its power spectrum for a given signal.\n",
        "    \"\"\"\n",
        "    dt = time[1] - time[0]  # Time step\n",
        "    N = len(signal)  # Number of samples\n",
        "    fs = 1 / dt  # Sampling frequency\n",
        "\n",
        "    # Compute FFT and its power spectrum\n",
        "    variance = np.std(signal) ** 2\n",
        "    f_values, fft_values = get_fft_values(signal, dt, N)\n",
        "    fft_power = variance * fft_values ** 2  # Compute power spectrum\n",
        "\n",
        "    # Create the plot\n",
        "    fig, ax = plt.subplots(figsize=(15, 3))\n",
        "    ax.plot(f_values, fft_values, 'r-', label='Fourier Transform')\n",
        "    ax.plot(f_values, fft_power, 'k--', linewidth=1, label='FFT Power Spectrum')\n",
        "    ax.set_xlabel('Frequency [Hz / year]', fontsize=18)\n",
        "    ax.set_ylabel('Amplitude', fontsize=18)\n",
        "    ax.set_title('Fourier Transform + Power Spectrum', fontsize=18)\n",
        "    ax.legend()\n",
        "    plt.show()\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "KxdFT-xQPChS"
      },
      "outputs": [],
      "source": [
        "\n",
        "dataset = \"http://paos.colorado.edu/research/wavelets/wave_idl/sst_nino3.dat\"\n",
        "df_nino = pd.read_table(dataset, header=None)\n",
        "N = df_nino.shape[0]\n",
        "t0=1871\n",
        "dt=0.25\n",
        "time = np.arange(0, N) * dt + t0\n",
        "signal = df_nino.values.squeeze()\n",
        "scales = np.arange(1, 128)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 251
        },
        "id": "YvwKQ0BePJoJ",
        "outputId": "7aa50346-fa7f-4f03-de20-b8fdd72b8680"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 1080x216 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "output_type": "display_data"
        }
      ],
      "source": [
        "\n",
        "plot_signal_plus_average(time, signal)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 232
        },
        "id": "gG3UuWTQPHJd",
        "outputId": "399d3824-b80b-4a8c-89f7-ca14db6879ea"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 1080x216 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "output_type": "display_data"
        }
      ],
      "source": [
        "\n",
        "plot_fft_plus_power(time, signal)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 688
        },
        "id": "BsafvQbUPba5",
        "outputId": "49c723cc-b65d-422a-8a48-37020e0c9f69"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/pywt/_cwt.py:74: FutureWarning: Wavelets from the family cmor, without parameters specified in the name are deprecated. The name should takethe form cmorB-C where B and C are floats representing the bandwidth frequency and center frequency, respectively (example: cmor1.5-1.0).\n",
            "  wavelet = DiscreteContinuousWavelet(wavelet)\n"
          ]
        },
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 1080x720 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "output_type": "display_data"
        }
      ],
      "source": [
        "\n",
        "plot_wavelet(time, signal, scales)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "qvQWDHjPUJ61"
      },
      "source": [
        "## Classification of signals using the CWT and CNN\n",
        "we have seen that the wavelet transform of a 1D signal results in a 2D scaleogram, which contains a lot more information than just the time series or the Fourier Transform. We have seen that when applied to the el-Nino dataset, it can tell us the period of the most considerable oscillations, when these oscillations were present, and when they were not.\n",
        "\n",
        "Such a scaleogram can be used to understand a system's dynamic behaviour better and to distinguish different types of signals produced by a system from each other.\n",
        "If you record a signal while walking up or down the stairs, the scaleograms will look different. ECG measurements of people with a healthy heart will have different scaleograms than ECG measurements of people with arrhythmia. Alternatively, measurements on a bearing, motor, rotor, ventilator, etc, are taken when it is faulty vs. when it is not faulty. The possibilities are limitless!\n",
        "\n",
        "So, by looking at the scaleograms, we can distinguish a broken motor from a working one, a healthy person from a sick one, a person walking up the stairs from a person walking down the stairs, etc. However, if you are as lazy as me, you probably do not want to manually sift through thousands of scaleograms. One way to automate this process is to build a Convolutional Neural Network, which can automatically detect the class each scaleogram belongs to and classify them accordingly."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "V5HNpwmlT_X9"
      },
      "outputs": [],
      "source": [
        "# Raw Data\n",
        "! wget http://archive.ics.uci.edu/ml/machine-learning-databases/00341/HAPT%20Data%20Set.zip\n",
        "! unzip HAPT\" \"Data\" \"Set.zip"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "jngebDqrp5GB"
      },
      "outputs": [],
      "source": [
        "! wget http://archive.ics.uci.edu/ml/machine-learning-databases/00341/HAPT%20Data%20Set.zip\n",
        "! unzip HAPT\" \"Data\" \"Set.zip"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "wopUO1fLcTzO"
      },
      "source": [
        "The raw data has three main signal types: total acceleration, body acceleration, and body gyroscope. Each has three axes of data. This means that there are nine variables for each time step.\n",
        "\n",
        "Additionally, every data series has been divided into 128-time increments or overlapping windows of 2.65 seconds of data. The preceding section's engineering feature windows (rows) match these data windows.\n",
        "\n",
        "This indicates that a single row of data has 1,152 elements (128 * 9). There is probably some redundant data, less than twice as large as the 561 element vectors in the preceding section."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 119
        },
        "id": "AeqMGF_EviSN",
        "outputId": "81d64c0f-12a8-4ff4-c5c2-f69e7ceb8899"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Downloading human-activity-recognition-with-smartphones.zip to /content\n",
            " 36% 9.00M/25.0M [00:00<00:00, 24.9MB/s]\n",
            "100% 25.0M/25.0M [00:00<00:00, 50.8MB/s]\n",
            "Archive:  human-activity-recognition-with-smartphones.zip\n",
            "  inflating: test.csv                \n",
            "  inflating: train.csv               \n"
          ]
        }
      ],
      "source": [
        "!mkdir -p ~/.kaggle\n",
        "!cp kaggle.json ~/.kaggle/\n",
        "! chmod 600 /root/.kaggle/kaggle.json\n",
        "\n",
        "! kaggle datasets download -d uciml/human-activity-recognition-with-smartphones\n",
        "! unzip human-activity-recognition-with-smartphones.zip"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "6y2utGVjviXg"
      },
      "outputs": [],
      "source": [
        "train=pd.read_csv('train.csv')\n",
        "test= pd.read_csv('test.csv')\n",
        "\n",
        "data = pd.concat([train, test], axis=0).reset_index(drop=True)\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "h7_tSBV1vicL"
      },
      "outputs": [],
      "source": [
        "labels = data.iloc[:,-1]\n",
        "data=data.drop(['subject','Activity'], axis=1)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "p5S_0dIbWFv6"
      },
      "outputs": [],
      "source": [
        "data.head()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "S9pIgmdrg1iJ"
      },
      "source": [
        "## ECG classifier"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "bqwhIh1cg1vw"
      },
      "outputs": [],
      "source": [
        "! wget https://github.com/mathworks/physionet_ECG_data/raw/master/ECGData.zip\n",
        "! unzip ECGData.zip"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "PbwBDmX6g65E"
      },
      "outputs": [],
      "source": [
        "import scipy.io as sio\n",
        "import scipy\n",
        "from collections import defaultdict, Counter\n",
        "from sklearn.ensemble import GradientBoostingClassifier\n",
        "from sklearn.preprocessing import StandardScaler, LabelEncoder\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.metrics import accuracy_score\n",
        "from sklearn.decomposition import PCA\n",
        "from sklearn.manifold import TSNE\n",
        "from sklearn.metrics import classification_report\n",
        "\n",
        "from lightgbm import LGBMClassifier\n",
        "from collections import Counter\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "pWN-aHzDg69d"
      },
      "outputs": [],
      "source": [
        "data=sio.loadmat('ECGData.mat')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "4kuOaZy0g10V"
      },
      "outputs": [],
      "source": [
        "ecg_signals= pd.DataFrame(data['ECGData'][0][0][0])\n",
        "ecg_labels= pd.Series(np.array(list(map(lambda x: str(x[0]), \n",
        "                                        np.squeeze(data['ECGData'][0][0][1])))), name='labels').astype('category')\n",
        "\n",
        "ecg_data=pd.concat([ecg_labels, ecg_signals],axis=1)\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 253
        },
        "id": "lMHhKzNPVw3Z",
        "outputId": "146aaacd-cf57-4e59-e716-faec77c4db4b"
      },
      "outputs": [
        {
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>labels</th>\n",
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              "      <th>1</th>\n",
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              "      <th>157</th>\n",
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              "      <td>-0.075</td>\n",
              "      <td>-0.165</td>\n",
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              "      <td>-0.505</td>\n",
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              "      <td>0.575</td>\n",
              "      <td>1.775</td>\n",
              "      <td>1.315</td>\n",
              "      <td>-0.195</td>\n",
              "      <td>-0.725</td>\n",
              "      <td>-0.495</td>\n",
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              "    <tr>\n",
              "      <th>158</th>\n",
              "      <td>NSR</td>\n",
              "      <td>-0.185</td>\n",
              "      <td>-0.155</td>\n",
              "      <td>-0.145</td>\n",
              "      <td>-0.135</td>\n",
              "      <td>-0.105</td>\n",
              "      <td>-0.095</td>\n",
              "      <td>-0.095</td>\n",
              "      <td>-0.065</td>\n",
              "      <td>-0.055</td>\n",
              "      <td>...</td>\n",
              "      <td>0.105</td>\n",
              "      <td>0.105</td>\n",
              "      <td>0.155</td>\n",
              "      <td>0.125</td>\n",
              "      <td>0.175</td>\n",
              "      <td>0.155</td>\n",
              "      <td>0.185</td>\n",
              "      <td>0.225</td>\n",
              "      <td>0.225</td>\n",
              "      <td>0.155</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>159</th>\n",
              "      <td>NSR</td>\n",
              "      <td>-0.355</td>\n",
              "      <td>-0.355</td>\n",
              "      <td>-0.345</td>\n",
              "      <td>-0.335</td>\n",
              "      <td>-0.335</td>\n",
              "      <td>-0.345</td>\n",
              "      <td>-0.345</td>\n",
              "      <td>-0.375</td>\n",
              "      <td>-0.365</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.125</td>\n",
              "      <td>-0.175</td>\n",
              "      <td>-0.225</td>\n",
              "      <td>-0.235</td>\n",
              "      <td>-0.275</td>\n",
              "      <td>-0.315</td>\n",
              "      <td>-0.355</td>\n",
              "      <td>-0.335</td>\n",
              "      <td>-0.315</td>\n",
              "      <td>-0.315</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>160</th>\n",
              "      <td>NSR</td>\n",
              "      <td>-0.275</td>\n",
              "      <td>-0.245</td>\n",
              "      <td>-0.285</td>\n",
              "      <td>-0.265</td>\n",
              "      <td>-0.235</td>\n",
              "      <td>-0.215</td>\n",
              "      <td>-0.165</td>\n",
              "      <td>-0.165</td>\n",
              "      <td>-0.145</td>\n",
              "      <td>...</td>\n",
              "      <td>0.015</td>\n",
              "      <td>-0.095</td>\n",
              "      <td>-0.075</td>\n",
              "      <td>-0.105</td>\n",
              "      <td>-0.145</td>\n",
              "      <td>-0.165</td>\n",
              "      <td>-0.165</td>\n",
              "      <td>-0.205</td>\n",
              "      <td>-0.145</td>\n",
              "      <td>-0.165</td>\n",
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              "    <tr>\n",
              "      <th>161</th>\n",
              "      <td>NSR</td>\n",
              "      <td>0.125</td>\n",
              "      <td>0.005</td>\n",
              "      <td>0.025</td>\n",
              "      <td>0.065</td>\n",
              "      <td>-0.085</td>\n",
              "      <td>0.005</td>\n",
              "      <td>-0.065</td>\n",
              "      <td>-0.015</td>\n",
              "      <td>-0.035</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.245</td>\n",
              "      <td>-0.225</td>\n",
              "      <td>-0.245</td>\n",
              "      <td>-0.275</td>\n",
              "      <td>-0.295</td>\n",
              "      <td>-0.275</td>\n",
              "      <td>-0.275</td>\n",
              "      <td>-0.225</td>\n",
              "      <td>-0.275</td>\n",
              "      <td>-0.205</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 65537 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "    labels      0      1      2      3      4      5      6      7      8  \\\n",
              "157    NSR -0.075 -0.165 -0.225 -0.175 -0.225 -0.225 -0.215 -0.185 -0.235   \n",
              "158    NSR -0.185 -0.155 -0.145 -0.135 -0.105 -0.095 -0.095 -0.065 -0.055   \n",
              "159    NSR -0.355 -0.355 -0.345 -0.335 -0.335 -0.345 -0.345 -0.375 -0.365   \n",
              "160    NSR -0.275 -0.245 -0.285 -0.265 -0.235 -0.215 -0.165 -0.165 -0.145   \n",
              "161    NSR  0.125  0.005  0.025  0.065 -0.085  0.005 -0.065 -0.015 -0.035   \n",
              "\n",
              "     ...    65526  65527  65528  65529  65530  65531  65532  65533  65534  \\\n",
              "157  ...   -0.165 -0.265 -0.505 -0.315  0.575  1.775  1.315 -0.195 -0.725   \n",
              "158  ...    0.105  0.105  0.155  0.125  0.175  0.155  0.185  0.225  0.225   \n",
              "159  ...   -0.125 -0.175 -0.225 -0.235 -0.275 -0.315 -0.355 -0.335 -0.315   \n",
              "160  ...    0.015 -0.095 -0.075 -0.105 -0.145 -0.165 -0.165 -0.205 -0.145   \n",
              "161  ...   -0.245 -0.225 -0.245 -0.275 -0.295 -0.275 -0.275 -0.225 -0.275   \n",
              "\n",
              "     65535  \n",
              "157 -0.495  \n",
              "158  0.155  \n",
              "159 -0.315  \n",
              "160 -0.165  \n",
              "161 -0.205  \n",
              "\n",
              "[5 rows x 65537 columns]"
            ]
          },
          "execution_count": 7,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "\n",
        "ecg_data.tail()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "tJPIz77LVelO"
      },
      "outputs": [],
      "source": [
        "def plot_ecg_signal(arr_type):\n",
        "    \n",
        "    \n",
        "    signal=ecg_data[ecg_data['labels']==arr_type].iloc[0,1:]\n",
        "    time=np.arange(0,len(signal),1)\n",
        "    \n",
        "    plt.plot(time[0:500],signal[0:500])\n",
        "    plt.xlabel('Time')\n",
        "    plt.ylabel('Amplitud')\n",
        "    plt.title(f'{arr_type}')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 376
        },
        "id": "rVrJtdsslMp3",
        "outputId": "383b3728-8280-4c46-a5f4-95e9ad7d7821"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 576x396 with 3 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "output_type": "display_data"
        }
      ],
      "source": [
        "plt.figure()\n",
        "plt.subplot(311)\n",
        "plot_ecg_signal('ARR')\n",
        "plt.subplot(312)\n",
        "plot_ecg_signal('CHF')\n",
        "plt.subplot(313)\n",
        "plot_ecg_signal('NSR')"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "OEMO63Paf8wp"
      },
      "source": [
        "### Classifier with Raw data"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "CSUXQj6Dft9H"
      },
      "outputs": [],
      "source": [
        "X_train, X_test, y_train, y_test = train_test_split(ecg_signals, ecg_labels, random_state=3)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "okgERmzDft16"
      },
      "outputs": [],
      "source": [
        "lgbm = LGBMClassifier(n_estimators=1000, random_state=3)\n",
        "lgbm = lgbm.fit(X_train, y_train)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 221
        },
        "id": "1KaV6f0Vftur",
        "outputId": "134b139f-5640-422a-b741-76bd733350ca"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Accuracy on testset:\t0.8049\n",
            "\n",
            "              precision    recall  f1-score   support\n",
            "\n",
            "         ARR       0.82      0.88      0.85        26\n",
            "         CHF       0.50      0.25      0.33         4\n",
            "         NSR       0.82      0.82      0.82        11\n",
            "\n",
            "   micro avg       0.80      0.80      0.80        41\n",
            "   macro avg       0.71      0.65      0.67        41\n",
            "weighted avg       0.79      0.80      0.79        41\n",
            "\n"
          ]
        }
      ],
      "source": [
        "y_pred=lgbm.predict(X_test)\n",
        "score = accuracy_score(y_true=y_test, y_pred=y_pred)\n",
        "print('Accuracy on testset:\\t{:.4f}\\n'.format(score))\n",
        "print(classification_report(y_test, y_pred))"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "6eSvO1C-YyLO"
      },
      "source": [
        "### Classifier with PCA"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "id": "IgrkSmQjlehj",
        "outputId": "01da197e-15d9-493e-bed7-ed822b0851fb"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "(121, 71)\n"
          ]
        }
      ],
      "source": [
        "scl = StandardScaler()\n",
        "pca_data = scl.fit_transform(ecg_signals)\n",
        "\n",
        "pca = PCA(n_components=0.9, random_state=3)\n",
        "pca_data = pca.fit_transform(pca_data)\n",
        "\n",
        "enc = LabelEncoder()\n",
        "label_encoded = enc.fit_transform(ecg_labels)\n",
        "\n",
        "X_train, X_test, y_train, y_test = train_test_split(pca_data, label_encoded, random_state=3)\n",
        "print(X_train.shape)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "x_4WrgpzyhhG"
      },
      "outputs": [],
      "source": [
        "lgbm = LGBMClassifier(n_estimators=2000, random_state=3)\n",
        "lgbm = lgbm.fit(X_train, y_train)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 221
        },
        "id": "-ywDgb6myhmb",
        "outputId": "5151e479-d4b7-4b95-a495-6ee021c03362"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Accuracy on testset:\t0.8049\n",
            "\n",
            "              precision    recall  f1-score   support\n",
            "\n",
            "           0       0.85      0.85      0.85        26\n",
            "           1       0.33      0.50      0.40         4\n",
            "           2       1.00      0.82      0.90        11\n",
            "\n",
            "   micro avg       0.80      0.80      0.80        41\n",
            "   macro avg       0.73      0.72      0.72        41\n",
            "weighted avg       0.84      0.80      0.82        41\n",
            "\n"
          ]
        }
      ],
      "source": [
        "y_pred=lgbm.predict(X_test)\n",
        "score = accuracy_score(y_true=y_test, y_pred=y_pred)\n",
        "print('Accuracy on testset:\\t{:.4f}\\n'.format(score))\n",
        "print(classification_report(y_test, y_pred))"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "rZ52trs4YrEZ"
      },
      "source": [
        "### Feature engineering"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "W4ZtlRKMNO9T"
      },
      "outputs": [],
      "source": [
        "dict_ecg_data = defaultdict(list)\n",
        "for ii, label in enumerate(ecg_labels.values):\n",
        "    dict_ecg_data[label].append(ecg_signals.values[ii])"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "PHnho2DC3L2x"
      },
      "outputs": [],
      "source": [
        "def calculate_entropy(list_values):\n",
        "    counter_values = Counter(list_values).most_common()\n",
        "    probabilities = [elem[1]/len(list_values) for elem in counter_values]\n",
        "    entropy=scipy.stats.entropy(probabilities)\n",
        "    return entropy\n",
        "\n",
        "def calculate_statistics(list_values):\n",
        "    n5 = np.nanpercentile(list_values, 5)\n",
        "    n25 = np.nanpercentile(list_values, 25)\n",
        "    n75 = np.nanpercentile(list_values, 75)\n",
        "    n95 = np.nanpercentile(list_values, 95)\n",
        "    median = np.nanpercentile(list_values, 50)\n",
        "    mean = np.nanmean(list_values)\n",
        "    std = np.nanstd(list_values)\n",
        "    var = np.nanvar(list_values)\n",
        "    rms = np.nanmean(np.sqrt(list_values**2))\n",
        "    return [n5, n25, n75, n95, median, mean, std, var, rms]\n",
        "\n",
        "def calculate_crossings(list_values):\n",
        "    zero_crossing_indices = np.nonzero(np.diff(np.array(list_values) > 0))[0]\n",
        "    no_zero_crossings = len(zero_crossing_indices)\n",
        "    mean_crossing_indices = np.nonzero(np.diff(np.array(list_values) > np.nanmean(list_values)))[0]\n",
        "    no_mean_crossings = len(mean_crossing_indices)\n",
        "    return [no_zero_crossings, no_mean_crossings]\n",
        "\n",
        "def get_features(list_values):\n",
        "    entropy = calculate_entropy(list_values)\n",
        "    crossings = calculate_crossings(list_values)\n",
        "    statistics = calculate_statistics(list_values)\n",
        "    return [entropy] + crossings + statistics\n",
        "  \n",
        "def get_ecg_features(ecg_data, ecg_labels, waveletname):\n",
        "    list_features = []\n",
        "    list_unique_labels = list(set(ecg_labels))\n",
        "    list_labels = [list_unique_labels.index(elem) for elem in ecg_labels]\n",
        "    for signal in ecg_data:\n",
        "        list_coeff = pywt.wavedec(signal, waveletname)\n",
        "        features = []\n",
        "        for coeff in list_coeff:\n",
        "            features += get_features(coeff)\n",
        "        list_features.append(features)\n",
        "    return list_features, list_labels\n",
        "  \n",
        "def get_train_test(df, y_col, x_cols, ratio):\n",
        "    \"\"\" \n",
        "    This method transforms a dataframe into a train and test set, for this you need to specify:\n",
        "    1. the ratio train : test (usually 0.7)\n",
        "    2. the column with the Y_values\n",
        "    \"\"\"\n",
        "    mask = np.random.rand(len(df)) < ratio\n",
        "    df_train = df[mask]\n",
        "    df_test = df[~mask]\n",
        "       \n",
        "    Y_train = df_train[y_col].values\n",
        "    Y_test = df_test[y_col].values\n",
        "    X_train = df_train[x_cols].values\n",
        "    X_test = df_test[x_cols].values\n",
        "    return df_train, df_test, X_train, Y_train, X_test, Y_test"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "id": "ZA4F5IFW4bH9",
        "outputId": "6102cd5b-dc57-41d1-8276-59d738bf6e87"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "(99, 156)\n"
          ]
        }
      ],
      "source": [
        "list_labels = []\n",
        "list_features = []\n",
        "for k, v in dict_ecg_data.items():\n",
        "    yval = list(dict_ecg_data.keys()).index(k)\n",
        "    for signal in v:\n",
        "        features = []\n",
        "        list_labels.append(yval)\n",
        "        list_coeff = pywt.wavedec(signal, 'sym5')\n",
        "        for coeff in list_coeff:\n",
        "            features += get_features(coeff)\n",
        "        list_features.append(features)\n",
        "df = pd.DataFrame(list_features)\n",
        "ycol = 'y'\n",
        "xcols = list(range(df.shape[1]))\n",
        "df.loc[:,ycol] = list_labels\n",
        "\n",
        "df_train, df_test, X_train, Y_train, X_test, Y_test = get_train_test(df, ycol, xcols, ratio = 0.5)\n",
        "print(X_train.shape)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "pGIsT4Bx2O8g"
      },
      "source": [
        "#### Gradient Boosting with Feature engineering 96.8% acc  "
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 255
        },
        "id": "gTK4sJW_N3MI",
        "outputId": "1ecf8cc4-1cb5-4bf1-f9a3-72938233d612"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "The Train Score is 1.0\n",
            "The Test Score is 0.9523809523809523\n",
            "Accuracy on testset:\t0.9524\n",
            "\n",
            "              precision    recall  f1-score   support\n",
            "\n",
            "           0       0.93      1.00      0.97        42\n",
            "           1       1.00      0.67      0.80         9\n",
            "           2       1.00      1.00      1.00        12\n",
            "\n",
            "   micro avg       0.95      0.95      0.95        63\n",
            "   macro avg       0.98      0.89      0.92        63\n",
            "weighted avg       0.96      0.95      0.95        63\n",
            "\n"
          ]
        }
      ],
      "source": [
        "cls = GradientBoostingClassifier(n_estimators=2000)\n",
        "cls.fit(X_train, Y_train)\n",
        "train_score = cls.score(X_train, Y_train)\n",
        "test_score = cls.score(X_test, Y_test)\n",
        "print(\"The Train Score is {}\".format(train_score))\n",
        "print(\"The Test Score is {}\".format(test_score))\n",
        "\n",
        "y_pred=GradientBoostingClassifier.predict(cls, X_test)\n",
        "score = accuracy_score(y_true=Y_test, y_pred=y_pred)\n",
        "print('Accuracy on testset:\\t{:.4f}\\n'.format(score))\n",
        "print(classification_report(Y_test, y_pred))"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "F2eNNex2RC5Q"
      },
      "source": [
        "#### LGBM with feature engineering 98% acc..."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "3UESeqbTRDDq"
      },
      "outputs": [],
      "source": [
        "%time\n",
        "lgbm = LGBMClassifier(n_estimators=2000, random_state=3)\n",
        "lgbm = lgbm.fit(X_train, Y_train)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 221
        },
        "id": "fouqJ3qFRDJ4",
        "outputId": "2e6a09e2-63ce-4c03-f489-bcd6d9b43d29"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Accuracy on testset:\t0.9841\n",
            "\n",
            "              precision    recall  f1-score   support\n",
            "\n",
            "           0       0.98      1.00      0.99        42\n",
            "           1       1.00      0.89      0.94         9\n",
            "           2       1.00      1.00      1.00        12\n",
            "\n",
            "   micro avg       0.98      0.98      0.98        63\n",
            "   macro avg       0.99      0.96      0.98        63\n",
            "weighted avg       0.98      0.98      0.98        63\n",
            "\n"
          ]
        }
      ],
      "source": [
        "y_pred=lgbm.predict(X_test)\n",
        "score = accuracy_score(y_true=Y_test, y_pred=y_pred)\n",
        "print('Accuracy on testset:\\t{:.4f}\\n'.format(score))\n",
        "print(classification_report(Y_test, y_pred))"
      ]
    }
  ],
  "metadata": {
    "colab": {
      "collapsed_sections": [],
      "include_colab_link": true,
      "name": "ECG-Signal-Classifier-with-Wavelet-Transform.ipynb",
      "provenance": [],
      "toc_visible": true
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}
